5.
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Preface
This book completely revises the earlier book entitled MPEG-2. It is an interesting insight into the rate at which this
technology progresses that this book was in preparation only a year after MPEG-2 was first published. The impetus
for the revision is, of course, MPEG-4 which is comprehensively covered here. The opportunity has also been
taken to improve a number of explanations and to add a chapter on applications of MPEG.
The approach of the book has not changed in the slightest. Compression is a specialist subject with its own library
of specialist terminology which is generally accompanied by a substantial amount of mathematics. I have always
argued that mathematics is only a form of shorthand, itself a compression technique! Mathematics describes but
does not explain, whereas this book explains and then describes.
A chapter of fundamentals is included to make the main chapters easier to follow. Also included are some
guidelines which have been found practically useful in getting the best out of compression systems.
The reader who has endured this book will be in a good position to tackle the MPEG standards documents
themselves, although these are not for the faint-hearted, especially the MPEG-4 documents which are huge and
impenetrable. One wonders what they will come up with next!

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Chapter 1: Introduction to compression
1.1 What is MPEG?
MPEG is actually an acronym for the Moving Pictures Experts Group which was formed by the ISO (International
Standards Organization) to set standards for audio and video compression and transmission.
Compression is summarized in Figure 1.1. It will be seen in (a) that the data rate is reduced at source by the
compressor. The compressed data are then passed through a communication channel and returned to the original
rate by the expander. The ratio between the source data rate and the channel data rate is called the compression
factor. The term coding gain is also used. Sometimes a compressor and expander in series are referred to as a
compander. The compressor may equally well be referred to as a coder and the expander a decoder in which case
the tandem pair may be called a codec.
Figure 1.1: In (a) a compression system consists of compressor or coder, a transmission channel and a matching
expander or decoder. The combination of coder and decoder is known as a codec. (b) MPEG is asymmetrical since
the encoder is much more complex than the decoder.
Where the encoder is more complex than the decoder, the system is said to be asymmetrical. Figure 1.1(b) shows
that MPEG works in this way. The encoder needs to be algorithmic or adaptive whereas the decoder is ‘dumb’ and
carries out fixed actions. This is advantageous in applications such as broadcasting where the number of
expensive complex encoders is small but the number of simple inexpensive decoders is large. In point-to-point
applications the advantage of asymmetrical coding is not so great.
The approach of the ISO to standardization in MPEG is novel because it is not the encoder which is standardized.
Figure 1.2(a) shows that instead the way in which a decoder shall interpret the bitstream is defined. A decoder
which can successfully interpret the bitstream is said to be compliant. Figure 1.2(b) shows that the advantage of
standardizing the decoder is that over time encoding algorithms can improve yet compliant decoders will continue
to function with them.
It should be noted that a compliant decoder must correctly be able to interpret every allowable bitstream, whereas
an encoder which produces a restricted subset of the possible codes can still be compliant.

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Figure 1.2: (a) MPEG defines the protocol of the bitstream between encoder and decoder. The decoder is defined
by implication, the encoder is left very much to the designer. (b) This approach allows future encoders of better
performance to remain compatible with existing decoders. (c) This approach also allows an encoder to produce a
standard bitstream while its technical operation remains a commercial secret.
The MPEG standards give very little information regarding the structure and operation of the encoder. Provided the
bitstream is compliant, any coder construction will meet the standard, although some designs will give better picture
quality than others. Encoder construction is not revealed in the bitstream and manufacturers can supply encoders
using algorithms which are proprietary and their details do not need to be published. A useful result is that there
can be competition between different encoder designs which means that better designs can evolve. The user will
have greater choice because different levels of cost and complexity can exist in a range of coders yet a compliant
decoder will operate with them all.
MPEG is, however, much more than a compression scheme as it also standardizes the protocol and syntax under
which it is possible to combine or multiplex audio data with video data to produce a digital equivalent of a television
program. Many such programs can be combined in a single multiplex and MPEG defines the way in which such
multiplexes can be created and transported. The definitions include the metadata which decoders require to
demultiplex correctly and which users will need to locate programs of interest.
As with all video systems there is a requirement for synchronizing or genlocking and this is particularly complex
when a multiplex is assembled from many signals which are not necessarily synchronized to one another.
1.2 Why compression is necessary
Compression, bit rate reduction, data reduction and source coding are all terms which mean basically the same
thing in this context. In essence the same (or nearly the same) information is carried using a smaller quantity or
rate of data. It should be pointed out that in audio compression traditionally means a process in which the dynamic
range of the sound is reduced. In the context of MPEG the same word means that the bit rate is reduced, ideally
leaving the dynamics of the signal unchanged. Provided the context is clear, the two meanings can co-exist without
a great deal of confusion.
There are several reasons why compression techniques are popular:
(a) Compression extends the playing time of a given storage device.

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(b) Compression allows miniaturization. With fewer data to store, the same playing time is obtained with smaller
hardware. This is useful in ENG (electronic news gathering) and consumer devices.
(c) Tolerances can be relaxed. With fewer data to record, storage density can be reduced making equipment which
is more resistant to adverse environments and which requires less maintenance.
(d) In transmission systems, compression allows a reduction in bandwidth which will generally result in a reduction
in cost. This may make possible a service which would be impracticable without it.
(e) If a given bandwidth is available to an uncompressed signal, compression allows faster than real-time
transmission in the same bandwidth.
(f) If a given bandwidth is available, compression allows a better-quality signal in the same bandwidth
1.3 MPEG-1, 2 and 4 contrasted
The first compression standard for audio and video was MPEG-1. Although many applications have been found,
MPEG-1 was basically designed to allow moving pictures and sound to be encoded into the bit rate of an audio
Compact Disc. The resultant Video-CD was quite successful but has now been superseded by DVD. In order to
meet the low bit requirement, MPEG-1 downsampled the images heavily as well as using picture rates of only 24–
30 Hz and the resulting quality was moderate.[1][2]
The subsequent MPEG-2 standard was considerably broader in scope and of wider appeal. For example, MPEG-2
supports interlace and HD whereas MPEG-1 did not. MPEG-2 has become very important because it has been
chosen as the compression scheme for both DVB (digital video broadcasting) and DVD (digital video disk).
Developments in standardizing scaleable and multi-resolution compression which would have become MPEG-3
were ready by the time MPEG-2 was ready to be standardized and so this work was incorporated into MPEG-2,
and as a result there is no MPEG-3 standard.[3]
MPEG-4 uses further coding tools with additional complexity to achieve higher compression factors than MPEG-2.
In addition to more efficient coding of video, MPEG-4 moves closer to computer graphics applications. In the more
complex Profiles, the MPEG-4 decoder effectively becomes a rendering processor and the compressed bitstream
describes three-dimensional shapes and surface texture. It is to be expected that MPEG-4 will become as
important to Internet and wireless delivery as MPEG-2 has become in DVD and DVB.[4]
[1]
ISO/IEC JTC1/SC29/WG11 MPEG, International standard ISO 11172, Coding of moving pictures and associated
audio for digital storage media up to 1.5 Mbits/s (1992)
[2]
LeGall, D., MPEG: a video compression standard for multimedia applications. Communications of the ACM, 34,
No.4, 46–58 (1991)
[3]
MPEG-2 Video Standard: ISO/IEC 13818–2: Information technology – generic coding of moving pictures and
associated audio information: Video (1996) (aka ITU-T Rec. H-262 (1996))
[4]
MPEG-4 Standard: ISO/IEC 14496–2: Information technology – coding of audio-visual objects: Amd.1 (2000)
1.4 Some applications of compression
The applications of audio and video compression are limitless and the ISO has done well to provide standards
which are appropriate to the wide range of possible compression products.
MPEG coding embraces video pictures from the tiny screen of a videophone to the high-definition images needed
for electronic cinema. Audio coding stretches from speech-grade mono to multichannel surround sound.
Figure 1.3 shows the use of a codec with a recorder. The playing time of the medium is extended in proportion to
the compression factor. In the case of tapes, the access time is improved because the length of tape needed for a
given recording is reduced and so it can be rewound more quickly. In the case of DVD (digital video disk aka digital
versatile disk) the challenge was to store an entire movie on one 12 cm disk. The storage density available with
today’s optical disk technology is such that consumer recording of conventional uncompressed video would be out
of the question.
In communications, the cost of data links is often roughly proportional to the data rate and so there is simple
economic pressure to use a high compression factor. However, it should be borne in mind that implementing the
codec also has a cost which rises with compression factor and so a degree of compromise will be inevitable.

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Figure 1.3: Compression can be used around a recording medium. The storage capacity may be increased or the
access time reduced according to the application.
In the case of video-on-demand, technology exists to convey full bandwidth video to the home, but to do so for a
single individual at the moment would be prohibitively expensive. Without compression, HDTV (high-definition
television) requires too much bandwidth. With compression, HDTV can be transmitted to the home in a similar
bandwidth to an existing analog SDTV channel. Compression does not make video-on- demand or HDTV possible;
it makes them economically viable.
In workstations designed for the editing of audio and/or video, the source material is stored on hard disks for rapid
access. Whilst top-grade systems may function without compression, many systems use compression to offset the
high cost of disk storage. In some systems a compressed version of the top-grade material may also be stored for
browsing purposes.
When a workstation is used for off-line editing, a high compression factor can be used and artifacts will be visible in
the picture. This is of no consequence as the picture is only seen by the editor who uses it to make an EDL (edit
decision list) which is no more than a list of actions and the timecodes at which they occur. The original
uncompressed material is then conformed to the EDL to obtain a high-quality edited work. When on- line editing is
being performed, the output of the workstation is the finished product and clearly a lower compression factor will
have to be used. Perhaps it is in broadcasting where the use of compression will have its greatest impact. There is
only one electromagnetic spectrum and pressure from other services such as cellular telephones makes efficient
use of bandwidth mandatory. Analog television broadcasting is an old technology and makes very inefficient use of
bandwidth. Its replacement by a compressed digital transmission is inevitable for the practical reason that the
bandwidth is needed elsewhere.
Fortunately in broadcasting there is a mass market for decoders and these can be implemented as low-cost
integrated circuits. Fewer encoders are needed and so it is less important if these are expensive. Whilst the cost of
digital storage goes down year on year, the cost of the electromagnetic spectrum goes up. Consequently in the
future the pressure to use compression in recording will ease whereas the pressure to use it in radio
communications will increase.
1.5 Lossless and perceptive coding
Although there are many different coding techniques, all of them fall into one or other of these categories. In
lossless coding, the data from the expander are identical bit-for-bit with the original source data. The so-called
‘stacker’ programs which increase the apparent capacity of disk drives in personal computers use lossless codecs.
Clearly with computer programs the corruption of a single bit can be catastrophic. Lossless coding is generally
restricted to compression factors of around 2:1.
It is important to appreciate that a lossless coder cannot guarantee a particular compression factor and the
communications link or recorder used with it must be able to function with the variable output data rate. Source
data which result in poor compression factors on a given codec are described as difficult. It should be pointed out
that the difficulty is often a function of the codec. In other words data which one codec finds difficult may not be
found difficult by another. Lossless codecs can be included in bit-error-rate testing schemes. It is also possible to
cascade or concatenate lossless codecs without any special precautions.
Higher compression factors are only possible with lossy coding in which data from the expander are not identical
bit-for-bit with the source data and as a result comparing the input with the output is bound to reveal differences.
Lossy codecs are not suitable for computer data, but are used in MPEG as they allow greater compression factors
than lossless codecs. Successful lossy codecs are those in which the errors are arranged so that a human viewer
or listener finds them subjectively difficult to detect. Thus lossy codecs must be based on an understanding of
psycho-acoustic and psycho-visual perception and are often called perceptive codes.
In perceptive coding, the greater the compression factor required, the more accurately must the human senses be
modelled. Perceptive coders can be forced to operate at a fixed compression factor. This is convenient for practical

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transmission applications where a fixed data rate is easier to handle than a variable rate. The result of a fixed
compression factor is that the subjective quality can vary with the ‘difficulty’ of the input material. Perceptive codecs
should not be concatenated indiscriminately especially if they use different algorithms. As the reconstructed signal
from a perceptive codec is not bit-for-bit accurate, clearly such a codec cannot be included in any bit error rate
testing system as the coding differences would be indistinguishable from real errors.
Although the adoption of digital techniques is recent, compression itself is as old as television. Figure 1.4 shows
some of the compression techniques used in traditional television systems.
Most video signals employ a non-linear relationship between brightness and the signal voltage which is known as
gamma. Gamma is a perceptive coding technique which depends on the human sensitivity to video noise being a
function of the brightness. The use of gamma allows the same subjective noise level with an eight-bit system as
would be achieved with a fourteen-bit linear system.
One of the oldest techniques is interlace, which has been used in analog television from the very beginning as a
primitive way of reducing bandwidth. As will be seen in Chapter 5, interlace is not without its problems, particularly
in motion rendering. MPEG-2 supports interlace simply because legacy interlaced signals exist and there is a
requirement to compress them. This should not be taken to mean that it is a good idea. "/>
Figure 1.4: Compression is as old as television. (a) Interlace is a primitive way of halving the bandwidth. (b) Colour
difference working invisibly reduces colour resolution. (c) Composite video transmits colour in the same bandwidth
as monochrome.
The generation of colour difference signals from RGB in video represents an application of perceptive coding. The
human visual system (HVS) sees no change in quality although the bandwidth of the colour difference signals is
reduced. This is because human perception of detail in colour changes is much less than in brightness changes.
This approach is sensibly retained in MPEG.
Composite video systems such as PAL, NTSC and SECAM are all analog compression schemes which embed a
subcarrier in the luminance signal so that colour pictures are available in the same bandwidth as monochrome. In
comparison with a linear-light progressive scan RGB picture, gamma-coded interlaced composite video has a
compression factor of about 10:1.
In a sense MPEG-2 can be considered to be a modern digital equivalent of analog composite video as it has most
of the same attributes. For example, the eight-field sequence of the PAL subcarrier which makes editing difficult
has its equivalent in the GOP (group of pictures) of MPEG.

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1.6 Compression principles
In a PCM digital system the bit rate is the product of the sampling rate and the number of bits in each sample and
this is generally constant.
Nevertheless the information rate of a real signal varies. In all real signals, part of the signal is obvious from what
has gone before or what may come later and a suitable receiver can predict that part so that only the true
information actually has to be sent. If the characteristics of a predicting receiver are known, the transmitter can omit
parts of the message in the knowledge that the receiver has the ability to re-create it. Thus all encoders must
contain a model of the decoder.
One definition of information is that it is the unpredictable or surprising element of data. Newspapers are a good
example of information because they only mention items which are surprising. Newspapers never carry items about
individuals who have not been involved in an accident as this is the normal case. Consequently the phrase ‘no
news is good news’ is remarkably true because if an information channel exists but nothing has been sent then it is
most likely that nothing remarkable has happened.
The unpredictability of the punch line is a useful measure of how funny a joke is. Often the build-up paints a certain
picture in the listener’s imagination, which the punch line destroys utterly. One of the author’s favourites is the one
about the newly married couple who didn’t know the difference between putty and petroleum jelly – their windows
fell out.
The difference between the information rate and the overall bit rate is known as the redundancy. Compression
systems are designed to eliminate as much of that redundancy as practicable or perhaps affordable. One way in
which this can be done is to exploit statistical predictability in signals. The information content or entropy of a
sample is a function of how different it is from the predicted value. Most signals have some degree of predictability.
A sine wave is highly predictable, because all cycles look the same. According to Shannon’s theory, any signal
which is totally predictable carries no information. In the case of the sine wave this is clear because it represents a
single frequency and so has no bandwidth.
At the opposite extreme a signal such as noise is completely unpredictable and as a result all codecs find noise
difficult. The most efficient way of coding noise is PCM. A codec which is designed using the statistics of real
material should not be tested with random noise because it is not a representative test. Second, a codec which
performs well with clean source material may perform badly with source material containing superimposed noise.
Most practical compression units require some form of pre-processing before the compression stage proper and
appropriate noise reduction should be incorporated into the pre-processing if noisy signals are anticipated. It will
also be necessary to restrict the degree of compression applied to noisy signals.
All real signals fall part-way between the extremes of total predictability and total unpredictability or noisiness. If the
bandwidth (set by the sampling rate) and the dynamic range (set by the wordlength) of the transmission system are
used to delineate an area, this sets a limit on the information capacity of the system. Figure 1.5(a) shows that most
real signals only occupy part of that area. The signal may not contain all frequencies, or it may not have full
dynamics at certain frequencies. "/>

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Figure 1.5: (a) A perfect coder removes only the redundancy from the input signal and results in subjectively
lossless coding. If the remaining entropy is beyond the capacity of the channel some of it must be lost and the
codec will then be lossy. An imperfect coder will also be lossy as it fails to keep all entropy. (b) As the compression
factor rises, the complexity must also rise to maintain quality. (c) High compression factors also tend to increase
latency or delay through the system.
Entropy can be thought of as a measure of the actual area occupied by the signal. This is the area that must be
transmitted if there are to be no subjective differences or artifacts in the received signal. The remaining area is
called the redundancy because it adds nothing to the information conveyed. Thus an ideal coder could be imagined
which miraculously sorts out the entropy from the redundancy and only sends the former. An ideal decoder would
then re-create the original impression of the information quite perfectly. As the ideal is approached, the coder
complexity and the latency or delay both rise. Figure 1.5(b) shows how complexity increases with compression
factor. The additional complexity of MPEG-4 over MPEG-2 is obvious from this. Figure 1.5(c) shows how increasing
the codec latency can improve the compression factor.
Obviously we would have to provide a channel which could accept whatever entropy the coder extracts in order to
have transparent quality. As a result moderate coding gains which only remove redundancy need not cause
artifacts and result in systems which are described as subjectively lossless. If the channel capacity is not sufficient
for that, then the coder will have to discard some of the entropy and with it useful information. Larger coding gains
which remove some of the entropy must result in artifacts. It will also be seen from Figure 1.5 that an imperfect
coder will fail to separate the redundancy and may discard entropy instead, resulting in artifacts at a sub-optimal
compression factor.
A single variable-rate transmission or recording channel is traditionally unpopular with channel providers, although
newer systems such as ATM support variable rate. Digital transmitters used in DVB have a fixed bit rate. The
variable rate requirement can be overcome by combining several compressed channels into one constant rate
transmission in a way which flexibly allocates data rate between the channels. Provided the material is unrelated,
the probability of all channels reaching peak entropy at once is very small and so those channels which are at one
instant passing easy material will make available transmission capacity for those channels which are handling
difficult material. This is the principle of statistical multiplexing.
Where the same type of source material is used consistently, e.g. English text, then it is possible to perform a
statistical analysis on the frequency with which particular letters are used. Variable-length coding is used in which
frequently used letters are allocated short codes and letters which occur infrequently are allocated long codes. This
results in a lossless code. The well-known Morse code used for telegraphy is an example of this approach. The
letter e is the most frequent in English and is sent with a single dot. An infrequent letter such as z is allocated a
long complex pattern. It should be clear that codes of this kind which rely on a prior knowledge of the statistics of
the signal are only effective with signals actually having those statistics. If Morse code is used with another
language, the transmission becomes significantly less efficient because the statistics are quite different; the letter z,
for example, is quite common in Czech.
The Huffman code is also one which is designed for use with a data source having known statistics. The probability
of the different code values to be transmitted is studied, and the most frequent codes are arranged to be

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transmitted with short wordlength symbols. As the probability of a code value falls, it will be allocated longer
wordlength.[5]
The Huffman code is used in conjunction with a number of compression techniques and is shown in Figure 1.6.
Figure 1.6: The Huffman code achieves compression by allocating short codes to frequent values. To aid
deserializing the short codes are not prefixes of longer codes.
The input or source codes are assembled in order of descending probability. The two lowest probabilities are
distinguished by a single code bit and their probabilities are combined. The process of combining probabilities is
continued until unity is reached and at each stage a bit is used to distinguish the path. The bit will be a zero for the
most probable path and one for the least. The compressed output is obtained by reading the bits which describe
which path to take going from right to left.
In the case of computer data, there is no control over the data statistics. Data to be recorded could be instructions,
images, tables, text files and so on; each having their own code value distributions. In this case a coder relying on
fixed source statistics will be completely inadequate. Instead a system is used which can learn the statistics as it
goes along. The Lempel– Ziv–Welch (LZW) lossless codes are in this category. These codes build up a conversion
table between frequent long source data strings and short transmitted data codes at both coder and decoder and
initially their compression factor is below unity as the contents of the conversion tables are transmitted along with
the data. However, once the tables are established, the coding gain more than compensates for the initial loss. In
some applications, a continuous analysis of the frequency of code selection is made and if a data string in the table
is no longer being used with sufficient frequency it can be deselected and a more common string substituted.
Lossless codes are less common for audio and video coding where perceptive codes are permissible. The
perceptive codes often obtain a coding gain by shortening the wordlength of the data representing the signal
waveform. This must increase the noise level and the trick is to ensure that the resultant noise is placed at
frequencies where human senses are least able to perceive it. As a result although the received signal is
measurably different from the source data, it can appear the same to the human listener or viewer at moderate
compressions factors. As these codes rely on the characteristics of human sight and hearing, they can only be fully
tested subjectively.
The compression factor of such codes can be set at will by choosing the wordlength of the compressed data.
Whilst mild compression will be undetectable, with greater compression factors, artifacts become noticeable. Figure
1.5 shows that this is inevitable from entropy considerations.
[5]
Huffman, D.A. A method for the construction of minimum redundancy codes. Proc. IRE, 40 1098–1101 (1952)
1.7 Video compression
Video signals exist in four dimensions: these are the attributes of the pixel, the horizontal and vertical spatial axes
and the time axis. Compression can be applied in any or all of those four dimensions. MPEG assumes an eight-bit
colour difference signal as the input, requiring rounding if the source is ten-bit. The sampling rate of the colour
signals is less than that of the luminance. This is done by downsampling the colour samples horizontally and
generally vertically as well. Essentially an MPEG system has three parallel simultaneous channels, one for
luminance and two colour difference, which after coding are multiplexed into a single bitstream.

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Figure 1.7: (a) Spatial or intra-coding works on individual images. (b) Temporal or inter-coding works on
successive images.
Figure 1.7(a) shows that when individual pictures are compressed without reference to any other pictures, the time
axis does not enter the process which is therefore described as intra-coded (intra = within) compression. The term
spatial coding will also be found. It is an advantage of intra-coded video that there is no restriction to the editing
which can be carried out on the picture sequence. As a result compressed VTRs such as Digital Betacam, DVC
and D-9 use spatial coding. Cut editing may take place on the compressed data directly if necessary. As spatial
coding treats each picture independently, it can employ certain techniques developed for the compression of still
pictures. The ISO JPEG (Joint Photographic Experts Group) compression standards are in this category. Where a
succession of JPEG coded images are used for television, the term ‘Motion JPEG’ will be found.[6][7]
Greater compression factors can be obtained by taking account of the redundancy from one picture to the next.
This involves the time axis, as Figure 1.7(b) shows, and the process is known as inter-coded (inter = between) or
temporal compression.
Temporal coding allows a higher compression factor, but has the disadvantage that an individual picture may exist
only in terms of the differences from a previous picture. Clearly editing must be undertaken with caution and
arbitrary cuts simply cannot be performed on the MPEG bitstream. If a previous picture is removed by an edit, the
difference data will then be insufficient to re-create the current picture.
1.7.1 Intra-coded compression
Intra-coding works in three dimensions on the horizontal and vertical spatial axes and on the sample values.
Analysis of typical television pictures reveals that whilst there is a high spatial frequency content due to detailed
areas of the picture, there is a relatively small amount of energy at such frequencies. Often pictures contain
sizeable areas in which the same or similar pixel values exist. This gives rise to low spatial frequencies. The
average brightness of the picture results in a substantial zero frequency component. Simply omitting the high-
frequency components is unacceptable as this causes an obvious softening of the picture.
A coding gain can be obtained by taking advantage of the fact that the amplitude of the spatial components falls
with frequency. It is also possible to take advantage of the eye’s reduced sensitivity to noise in high spatial
frequencies. If the spatial frequency spectrum is divided into frequency bands the high-frequency bands can be
described by fewer bits not only because their amplitudes are smaller but also because more noise can be
tolerated. The wavelet transform (MPEG-4 only) and the discrete cosine transform used in JPEG and MPEG-1,
MPEG-2 and MPEG-4 allow two-dimensional pictures to be described in the frequency domain and these are
discussed in Chapter 3.
1.7.2 Inter-coded compression

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Inter-coding takes further advantage of the similarities between successive pictures in real material. Instead of
sending information for each picture separately, inter-coders will send the difference between the previous picture
and the current picture in a form of differential coding.
Figure 1.8 shows the principle. A picture store is required at the coder to allow comparison to be made between
successive pictures and a similar store is required at the decoder to make the previous picture available.
Figure 1.8: An inter-coded system (a) uses a delay to calculate the pixel differences between successive pictures.
To prevent error propagation, intra-coded pictures (b) may be used periodically.
The difference data may be treated as a picture itself and subjected to some form of transform-based spatial
compression.
The simple system of Figure 1.8(a) is of limited use as in the case of a transmission error, every subsequent picture
would be affected. Channel switching in a television set would also be impossible. In practical systems a
modification is required. One approach is the so-called ‘leaky predictor’ in which the next picture is predicted from a
limited number of previous pictures rather than from an indefinite number. As a result errors cannot propagate
indefinitely. The approach used in MPEG is that periodically some absolute picture data are transmitted in place of
difference data.
Figure 1.8(b) shows that absolute picture data, known as I or intra pictures are interleaved with pictures which are
created using difference data, known as P or predicted pictures. The I pictures require a large amount of data,
whereas the P pictures require fewer data. As a result the instantaneous data rate varies dramatically and buffering
has to be used to allow a constant transmission rate. The leaky predictor needs less buffering as the compression
factor does not change so much from picture to picture.
The I picture and all of the P pictures prior to the next I picture are called a group of pictures (GOP). For a high
compression factor, a large number of P pictures should be present between I pictures, making a long GOP.
However, a long GOP delays recovery from a transmission error.
The compressed bitstream can only be edited at I pictures as shown.
In the case of moving objects, although their appearance may not change greatly from picture to picture, the data
representing them on a fixed sampling grid will change and so large differences will be generated between
successive pictures. It is a great advantage if the effect of motion can be removed from difference data so that they
only reflect the changes in appearance of a moving object since a much greater coding gain can then be obtained.
This is the objective of motion compensation. "/>
1.7.3 Introduction to motion compensation

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In real television program material objects move around before a fixed camera or the camera itself moves. Motion
compensation is a process which effectively measures motion of objects from one picture to the next so that it can
allow for that motion when looking for redundancy between pictures. Figure 1.9 shows that moving pictures can be
expressed in a three-dimensional space which results from the screen area moving along the time axis. In the case
of still objects, the only motion is along the time axis. However, when an object moves, it does so along the optic
flow axis which is not parallel to the time axis. The optic flow axis is the locus of a point on a moving object as it
takes on various screen positions.
Figure 1.9: Objects travel in a three-dimensional space along the optic flow axis which is only parallel to the time
axis if there is no movement.
It will be clear that the data values representing a moving object change with respect to the time axis. However,
looking along the optic flow axis the appearance of an object only changes if it deforms, moves into shadow or
rotates. For simple translational motions the data representing an object are highly redundant with respect to the
optic flow axis. Thus if the optic flow axis can be located, coding gain can be obtained in the presence of motion.
A motion-compensated coder works as follows. A reference picture is sent, but is also locally stored so that it can
be compared with another picture to find motion vectors for various areas of the picture. The reference picture is
then shifted according to these vectors to cancel inter- picture motion. The resultant predicted picture is compared
with the actual picture to produce a prediction error also called a residual. The prediction error is transmitted with
the motion vectors. At the receiver the reference picture is also held in a memory. It is shifted according to the
transmitted motion vectors to re-create the predicted picture and then the prediction error is added to it to re-create
the original.
In prior compression schemes the predicted picture followed the reference picture. In MPEG this is not the case.
Information may be brought back from a later picture or forward from an earlier picture as appropriate.
Figure 1.10: Telecine machines must use 3:2 pulldown to produce 60 Hz field rate video.
1.7.4 Film-originated video compression
Film can be used as the source of video signals if a telecine machine is used. The most common frame rate for film
is 24 Hz, whereas the field rates of television are 50 Hz and 60 Hz. This incompatibility is patched over in two
different ways. In 50 Hz telecine, the film is simply played slightly too fast so that the frame rate becomes 25 Hz.
Then each frame is converted into two television fields giving the correct 50 Hz field rate. In 0 Hz telecine, the film
travels at the correct speed, but alternate frames are used to produce two fields then three fields. The technique is

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known as 3:2 pulldown. In this way two frames produce five fields and so the correct 60 Hz field rate results. The
motion portrayal of telecine is not very good as moving objects judder, especially in 60 Hz systems. Figure 1.10
shows how the optic flow is portrayed in film-originated video.
When film-originated video is input to a compression system, the disturbed optic flow will play havoc with the
motion-compensation system. In a 50 Hz system there appears to be no motion between the two fields which have
originated from the same film frame, whereas between the next two fields large motions will exist. In 60 Hz
systems, the motion will be zero for three fields out of five.
With such inputs, it is more efficient to adopt a different processing mode which is based upon the characteristics of
the original film. Instead of attempting to manipulate fields of video, the system de-interlaces pairs of fields in order
to reconstruct the original film frames. This can be done by a fairly simple motion detector. When substantial motion
is measured between successive fields in the output of a telecine, this is taken to mean that the fields have come
from different film frames. When negligible motion is detected between fields, this is taken to indicate that the fields
have come from the same film frame.
In 50 Hz video it is quite simple to find the sequence and produce deinterlaced frames at 25 Hz. In 60 Hz 3:2
pulldown video the problem is slightly more complex because it is necessary to locate the frames in which three
fields are output so that the third field can be discarded, leaving, once more, de-interlaced frames at 25 Hz. Whilst
it is relatively straightforward to lock-on to the 3:2 sequence with direct telecine output signals, if the telecine
material has been edited on videotape the 3:2 sequence may contain discontinuities. In this case it is necessary to
provide a number of field stores in the de-interlace unit so that a series of fields can be examined to locate the
edits. Once telecine video has been de-interlaced back to frames, intra- and inter-coded compression can be
employed using frame-based motion compensation.
MPEG transmissions include flags which tell the decoder the origin of the material. Material originating at 24 Hz but
converted to interlaced video does not have the motion attributes of interlace because the lines in two fields have
come from the same point on the time axis. Two fields can be combined to create a progressively scanned frame.
In the case of 3:2 pulldown material, the third field need not be sent at all as the decoder can easily repeat a field
from memory. As a result the same compressed film material can be output at 50 or 60 Hz as required.
Recently conventional telecine machines have been superseded by the datacine which scans each film frame into
a pixel array which can be made directly available to the MPEG encoder without passing through an intermediate
digital video standard. Datacines are used extensively for mastering DVDs from film stock.
[6]
ISO Joint Photographic Experts Group standard JPEG-8-R8
[7]
Wallace, G.K., Overview of the JPEG (ISO/CCITT) still image compression standard. ISO/JTC1/SC2/WG8 N932
(1989)
1.8 Introduction to MPEG-1
As mentioned above, the intention of MPEG-1 is to deliver video and audio at the same bit rate as a conventional
audio CD. As the bit rate was a given, this was achieved by subsampling to half the definition of conventional
television. In order to have a constant input bit rate irrespective of the frame rate, 25 Hz systems have a picture
size of 352 × 288 pixels whereas 30 Hz systems have a picture size of 352 × 240 pixels. This is known as common
intermediate format (CIF). If the input is conventional interlaced video, CIF can be obtained by discarding alternate
fields and downsampling the remaining active lines by a factor of two.
As interlaced systems have very poor vertical resolution, down- sampling to CIF actually does little damage to still
images, although the very low picture rates damage motion portrayal.
Although MPEG-1 appeared rather rough on screen, this was due to the very low bit rate. It is more important to
appreciate that MPEG-1 introduced the great majority of the coding tools which would continue to be used in
MPEG-2 and MPEG-4. These included an elementary stream syntax, bidirectional motion-compensated coding,
buffering and rate control. Many of the spatial coding principles of MPEG-1 were taken from JPEG. MPEG-1 also
specified audio compression of up to two channels.
1.9 MPEG-2: Profiles and Levels
MPEG-2 builds upon MPEG-1 by adding interlace capability as well as a greatly expanded range of picture sizes
and bit rates. The use of scaleable systems is also addressed, along with definitions of how multiple MPEG
bitstreams can be multiplexed. As MPEG-2 is an extension of MPEG-1, it is easy for MPEG-2 decoders to handle

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MPEG-1 data. In a sense an MPEG-1 bitstream is an MPEG-2 bitstream which has a restricted vocabulary and so
can be readily understood by an MPEG-2 decoder.
MPEG-2 has too many applications to solve with a single standard and so it is subdivided into Profiles and Levels.
Put simply a Profile describes a degree of complexity whereas a Level describes the picture size or resolution
which goes with that Profile. Not all Levels are supported at all Profiles. Figure 1.11 shows the available
combinations. In principle there are twenty-four of these, but not all have been defined. An MPEG-2 decoder
having a given Profile and Level must also be able to decode lower Profiles and Levels.
Figure 1.11: Profiles and Levels in MPEG-2. See text for details.
The simple Profile does not support bidirectional coding and so only I and P pictures will be output. This reduces
the coding and decoding delay and allows simpler hardware. The simple Profile has only been defined at Main
Level (SP ML).
The Main Profile is designed for a large proportion of uses. The Low Level uses a low resolution input having only
352 pixels per line. The majority of broadcast applications will require the MP ML (Main Profile at Main Level)
subset of MPEG which supports SDTV (standard definition television). The High-1440 Level is a high-definition
scheme which doubles the definition compared to Main Level. The High Level not only doubles the resolution but
maintains that resolution with 16:9 format by increasing the number of horizontal samples from 1440 to 1920.
In compression systems using spatial transforms and requantizing it is possible to produce scaleable signals. A
scaleable process is one in which the input results in a main signal and a ‘helper’ signal. The main signal can be
decoded alone to give a picture of a certain quality, but if the information from the helper signal is added some
aspect of the quality can be improved.
Figure 1.12(a) shows that in a conventional MPEG coder, by heavily requantizing coefficients a picture with
moderate signal-to-noise ratio results. If, however, that picture is locally decoded and subtracted pixel by pixel from
the original, a ‘quantizing noise’ picture would result. This can be compressed and transmitted as the helper signal.
A simple decoder only decodes the main ‘noisy’ bitstream, but a more complex decoder can decode both
bitstreams and combine them to produce a low- noise picture. This is the principle of SNR scaleability.
Figure 1.12: (a) An SNR scaleable encoder produces a ‘noisy’ signal and a noise cancelling signal. (b) A spatially
scaleable encoder produces a low-resolution picture and a resolution-enhancing picture.

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As an alternative, Figure 1.12(b) shows that by coding only the lower spatial frequencies in a HDTV picture a base
bitstream can be made which an SDTV receiver can decode. If the lower definition picture is locally decoded and
subtracted from the original picture, a ‘definition- enhancing’ picture would result. This can be coded into a helper
signal. A suitable decoder could combine the main and helper signals to re- create the HDTV picture. This is the
principle of spatial scaleability.
The High Profile supports both SNR and spatial scaleability as well as allowing the option of 4:2:2 sampling (see
Section 2.11).
The 4:2:2 Profile has been developed for improved compatibility with existing digital television production
equipment. This allows 4:2:2 working without requiring the additional complexity of using the High Profile. For
example a HP ML decoder must support SNR scaleability which is not a requirement for production.
MPEG-2 increased the number of audio channels possible to five whilst remaining compatible with MPEG-1 audio.
MPEG-2 subsequently introduced a more efficient audio coding scheme known as MPEG-2 AAC (advanced audio
coding) which is not backwards compatible with the earlier audio coding schemes.
1.10 Introduction to MPEG-4
MPEG-4 introduces a number of new coding tools as shown in Figure 1.13. In MPEG-1 and MPEG-2 the motion
compensation is based on regular fixed-size areas of image known as macroblocks. Whilst this works well at the
designed bit rates, there will always be some inefficiency due to real moving objects failing to align with macroblock
boundaries. This will increase the residual bit rate. In MPEG-4, moving objects can be coded as arbitrary shapes.
Figure 1.14 shows that a background can be coded quite independently from objects in front of it. Object motion
can then be described with vectors and much-reduced residual data. According to the Profile, objects may be two-
dimensional, three- dimensional and opaque or translucent. The decoder must contain effectively a layering vision
mixer which is capable of prioritizing image data as a function of how close it is to the viewer. The picture coding of
MPEG-4 is known as texture coding and is more advanced than the MPEG-2 equivalent, using more lossless
predictive coding for pixel values, coefficients and vectors.
Figure 1.13: MPEG-4 introduces a number of new coding tools over those of earlier MPEG standards. These
include object coding, mesh coding, still picture coding and face and body animation.
Figure 1.14: (a) In MPEG-1 and MPEG-2, computer graphic images must be rendered to video before coding. (b)

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In contrast, MPEG-4 may move the rendering process to the decoder, reducing the bit rate needed with the penalty
of increased decoder complexity.
In addition to motion compensation, MPEG-4 can describe how an object changes its perspective as it moves
using a technique called mesh coding. By warping another image, the prediction of the present image is improved.
MPEG-4 also introduces coding for still images using DCT or wavelets.
Although MPEG-2 supported some scaleability, MPEG-4 also takes this further. In addition to spatial and noise
scaleability, MPEG-4 also allows temporal scaleability where a base level bitstream having a certain frame rate
may be augmented by an additional enhancement bitstream to produce a decoder output at a higher frame rate.
This is important as it allows a way forward from the marginal frame rates of today’s film and television formats
whilst remaining backwards compatible with traditional equipment. The comprehensive scaleability of MPEG-4 is
equally important in networks where it allows the user the best picture possible for the available bit rate.
MPEG-4 also introduces standards for face and body animation. Specialized vectors allow a still picture of a face
and optionally a body to be animated to allow expressions and gestures to accompany speech at very low bit rates.
In some senses MPEG-4 has gone upstream of the video signal which forms the input to MPEG-1 and MPEG-2
coders to analyse ways in which the video signal was rendered. Figure 1.14(a) shows that in a system using
MPEG-1 and MPEG-2, all rendering and production steps take place before the encoder. Figure 1.14(b) shows that
in MPEG-4, some of these steps can take place in the decoder. The advantage is that fewer data need to be
transmitted. Some of these data will be rendering instructions which can be very efficient and result in a high
compression factor. As a significant part of the rendering takes place in the decoder, computer graphics generators
can be designed directly to output an MPEG-4 bitstream. In interactive systems such as simulators and video
games, inputs from the user can move objects around the screen. The disadvantage is increased decoder
complexity, but as the economics of digital processing continues to advance this is hardly a serious concern.
As might be expected, the huge range of coding tools in MPEG-4 is excessive for many applications. As with
MPEG-2 this has been dealt with using Profiles and Levels. Figure 1.15 shows the range of Visual
Figure 1.15: The visual object types supported by MPEG-4 in versions 1 and 2.
Object types in version 1 of MPEG-4 and as expanded in version 2. For each visual object type the coding tools
needed is shown. Figure 1.16 shows the relationship between the Visual Profiles and the Visual Object types
supported by each Profile. The crossover between computergenerated and natural images is evident in the Profile
structure where Profiles 1–5 cover natural images, Profiles 8 and 9 cover rendered images and Profiles 6 and 7
cover hybrid natural/rendered images. It is only possible to give an introduction here and more detail is provided in
Chapter 5. MPEG-4 also extends the boundaries of audio coding. The MPEG-2 AAC technique is extended in
MPEG-4 by some additional tools. New tools are added which allow operation at very low bit rates for speech
applications. Also introduced is the concept of structured audio in which the audio waveform is synthesized at the
decoder from a bitstream which is essentially a digital musical score.

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Figure 1.16: The visual object types supported by each visual profile of MPEG-4.
1.11 Audio compression
Perceptive coding in audio relies on the principle of auditory masking, which is treated in detail in section 4.1.
Masking causes the ear/brain combination to be less sensitive to sound at one frequency in the presence of
another at a nearby frequency. If a first tone is present in the input, then it will mask signals of lower level at nearby
frequencies. The quantizing of the first tone and of further tones at those frequencies can be made coarser. Fewer
bits are needed and a coding gain results. The increased quantizing error is allowable if it is masked by the
presence of the first tone.
1.11.1 Sub-band coding
Sub-band coding mimics the frequency analysis mechanism of the ear and splits the audio spectrum into a large
number of different bands.
Signals in these bands can then be quantized independently. The quantizing error which results is confined to the
frequency limits of the band and so it can be arranged to be masked by the program material.
The techniques used in Layers I and II of MPEG audio are based on sub- band coding as are those used in DCC
(Digital Compact Cassette).
1.11.2 Transform coding
In transform coding the time-domain audio waveform is converted into a frequency domain representation such as
a Fourier, discrete cosine or wavelet transform (see Chapter 3). Transform coding takes advantage of the fact that
the amplitude or envelope of an audio signal changes relatively slowly and so the coefficients of the transform can
be transmitted relatively infrequently. Clearly such an approach breaks down in the presence of transients and
adaptive systems are required in practice. Transients cause the coefficients to be updated frequently whereas in
stationary parts of the signal such as sustained notes the update rate can be reduced. Discrete cosine transform
(DCT) coding is used in Layer III of MPEG audio and in the compression system of the Sony MiniDisc.
1.11.3 Predictive coding
In a predictive coder there are two identical predictors, one in the coder and one in the decoder. Their job is to
examine a run of previous data values and to extrapolate forward to estimate or predict what the next value will be.
This is subtracted from the actual next code value at the encoder to produce a prediction error which is transmitted.
The decoder then adds the prediction error to its own prediction to obtain the output code value again.
Prediction can be used in the time domain, where sample values are predicted, or in the frequency domain where
coefficient values are predicted. Time-domain predictive coders work with a short encode and decode delay and
are useful in telephony where a long loop delay causes problems. Frequency prediction is used in AC-3 and MPEG
AAC.
1.12 MPEG bitstreams

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MPEG supports a variety of bitstream types for various purposes and these are shown in Figure 1.17. The output
of a single compressor (video or audio) is known as an elementary stream. In transmission, many elementary
streams will be combined to make a transport stream. Multiplexing requires blocks or packets of constant size. It is
advantageous if these are short so that each elementary stream in the multiplex can receive regular data. A
transport stream has a complex structure because it needs to incorporate metadata indicating which audio
elementary streams and ancillary data are associated with which video elementary stream. It is possible to have a
single program transport stream (SPTS) which carries only the elementary streams of one TV program.
Figure 1.17: The bitstream types of MPEG-2. See text for details.
For certain purposes, such as recording a single elementary stream, the transport stream is not appropriate. The
small packets of the transport stream each require a header and this wastes storage space. In this case a program
stream can be used. A program stream is a simplified bitstream which multiplexes audio and video for a single
program together, provided they have been encoded from a common locked clock. Unlike a transport stream, the
blocks are larger and are not necessarily of fixed size.
1.13 Drawbacks of compression
By definition, compression removes redundancy from signals. Redundancy is, however, essential to making data
resistant to errors. As a result, compressed data are more sensitive to errors than uncompressed data. Thus
transmission systems using compressed data must incorporate more powerful error-correction strategies and avoid
compression techniques which are notoriously sensitive. As an example, the Digital Betacam format uses relatively
mild compression and yet requires 20 per cent redundancy whereas the D-5 format does not use compression and
only requires 17 per cent redundancy even though it has a recording density 30 per cent higher. Techniques using
tables such as the Lempel– Ziv–Welch codes are very sensitive to bit errors as an error in the transmission of a
table value results in bit errors every time that table location is accessed. This is known as error propagation.
Variable-length techniques such as the Huffman code are also sensitive to bit errors. As there is no fixed symbol
size, the only way the decoder can parse a serial bitstream into symbols is to increase the assumed wordlength a
bit at a time until a code value is recognized. The next bit must then be the first bit in the next symbol. A single bit in
error could cause the length of a code to be wrongly assessed and then all subsequent codes would also be
wrongly decoded until synchronization could be re-established. Later variable-length codes sacrifice some
compression efficiency in order to offer better resynchronization properties.
In non-real-time systems such as computers an uncorrectable error results in reference to the back-up media. In
real-time systems such as audio and video this is impossible and concealment must be used. However,
concealment relies on redundancy and compression reduces the degree of redundancy. Media such as hard disks
can be verified so that uncorrectable errors are virtually eliminated, but tape is prone to dropouts which will exceed
the burst-correcting power of the replay system from time to time. For this reason the compression factors used on
audio or video tape should be moderate.
As perceptive coders introduce noise, it will be clear that in a concatenated system the second codec could be
confused by the noise due to the first. If the codecs are identical then each may well make, or better still be
designed to make, the same decisions when they are in tandem. If the codecs are not identical the results could be
disappointing. Signal manipulation between codecs can also result in artifacts which were previously undetectable
becoming visible because the signal which was masking them is no longer present.

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In general, compression should not be used for its own sake, but only where a genuine bandwidth or cost
bottleneck exists. Even then the mildest compression possible should be used. Whilst high compression factors are
permissible for final delivery of material to the consumer, they are not advisable prior to any post-production
stages. For contribution material, lower compression factors are essential and this is sometimes referred to as
mezzanine level compression.
One practical drawback of compression systems is that they are largely generic in structure and the same
hardware can be operated at a variety of compression factors. Clearly the higher the compression factor, the
cheaper the system will be to operate so there will be economic pressure to use high compression factors.
Naturally the risk of artifacts is increased and so there is (or should be) counterpressure from those with
engineering skills to moderate the compression. The way of the world at the time of writing is that the accountants
have the upper hand. This was not a problem when there were fixed standards such as PAL and NTSC, as there
was no alternative but to adhere to them. Today there is plenty of evidence that the variable compression factor
control is being turned too far in the direction of economy.
It has been seen above that concatenation of compression systems should be avoided as this causes generation
loss. Generation loss is worse if the codecs are different. Interlace is a legacy compression technique and if
concatenated with MPEG, generation loss will be exaggerated. In theory and in practice better results are obtained
in MPEG for the same bit rate if the input is progressively scanned. Consequently the use of interlace with MPEG
coders cannot be recommended for new systems. Chapter 5 explores this theme in greater detail.
1.14 Compression pre-processing
Compression relies completely on identifying redundancy in the source material. Consequently anything which
reduces that redundancy will have a damaging effect. Noise is particularly undesirable as it creates additional
spatial frequencies in individual pictures as well as spurious differences between pictures. Where noisy source
material is anticipated some form of noise reduction will be essential.
When high compression factors must be used to achieve a low bit rate, it is inevitable that the level of artifacts will
rise. In order to contain the artifact level, it is necessary to restrict the source entropy prior to the coder. This may
be done by spatial low-pass filtering to reduce the picture resolution, and may be combined with downsampling to
reduce the number of pixels per picture. In some cases, such as teleconferencing, it will also be necessary to
reduce the picture rate. At very low bit rates the use of interlace becomes acceptable as a pre-processing stage
providing downsampling prior to the MPEG compression.
A compression pre-processor will combine various types of noise reduction (see Chapter 3) with spatial and
temporal downsampling.
1.15 Some guidelines
Although compression techniques themselves are complex, there are some simple rules which can be used to
avoid disappointment. Used wisely, MPEG compression has a number of advantages. Used in an inappropriate
manner, disappointment is almost inevitable and the technology could get a bad name. The next few points are
worth remembering.
Compression technology may be exciting, but if it is not necessary it should not be used.
If compression is to be used, the degree of compression should be as small as possible; i.e. use the
highest practical bit rate.
Cascaded compression systems cause loss of quality and the lower the bit rates, the worse this gets.
Quality loss increases if any post- production steps are performed between compressions.
Avoid using interlaced video with MPEG.
Compression systems cause delay.
Compression systems work best with clean source material. Noisy signals or poorly decoded composite
video give poor results.
Compressed data are generally more prone to transmission errors than non-compressed data. The choice
of a compression scheme must consider the error characteristics of the channel.
Audio codecs need to be level calibrated so that when sound pressure level-dependent decisions are made
in the coder those levels actually exist at the microphone.
Low bit rate coders should only be used for the final delivery of post- produced signals to the end-user.
Don’t believe statements comparing codec performance to ‘VHS quality’ or similar. Compression artifacts
are quite different from the artifacts of consumer VCRs.
Quality varies wildly with source material. Beware of ‘convincing’ demonstrations which may use selected
material to achieve low bit rates. Use your own test material, selected for a balance of difficulty.
Don’t be browbeaten by the technology. You don’t have to understand it to assess the results. Your eyes
and ears are as good as anyone’s so don’t be afraid to criticize artifacts. In the case of video, use still frames
to distinguish spatial artifacts from temporal ones.

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Chapter 2: Fundamentals
2.1 What is an audio signal?
Actual sounds are converted to electrical signals for convenience of handling, recording and conveying from one
place to another. This is the job of the microphone. There are two basic types of microphone, those which measure
the variations in air pressure due to sound, and those which measure the air velocity due to sound, although there
are numerous practical types which are a combination of both.
The sound pressure or velocity varies with time and so does the output voltage of the microphone, in proportion.
The output voltage of the microphone is thus an analog of the sound pressure or velocity.
As sound causes no overall air movement, the average velocity of all sounds is zero, which corresponds to silence.
As a result the bi-directional air movement gives rise to bipolar signals from the microphone, where silence is in the
centre of the voltage range, and instantaneously negative or positive voltages are possible. Clearly the average
voltage of all audio signals is also zero, and so when level is measured, it is necessary to take the modulus of the
voltage, which is the job of the rectifier in the level meter. When this is done, the greater the amplitude of the audio
signal, the greater the modulus becomes, and so a higher level is displayed.
Whilst the nature of an audio signal is very simple, there are many applications of audio, each requiring different
bandwidth and dynamic range.
2.2 What is a video signal?
The goal of television is to allow a moving picture to be seen at a remote place. The picture is a two-dimensional
image, which changes as a function of time. This is a three-dimensional information source where the dimensions
are distance across the screen, distance down the screen and time. Whilst telescopes convey these three
dimensions directly, this cannot be done with electrical signals or radio transmissions, which are restricted to a
single parameter varying with time.
The solution in film and television is to convert the three-dimensional moving image into a series of still pictures,
taken at the frame rate, and then, in television only, the two-dimensional images are scanned as a series of lines[1]
to produce a single voltage varying with time which can be digitized, recorded or transmitted. Europe, the Middle
East and the former Soviet Union use the scanning standard of 625/50, whereas the USA and Japan use
525/59.94.
[1]
Watkinson, J.R., Television Fundamentals, Oxford: Focal Press (1998)
2.3 Types of video
Figure 2.1 shows some of the basic types of analog colour video. Each of these types can, of course, exist in a
variety of line standards. Since practical colour cameras generally have three separate sensors, one for each
primary colour, an RGB component system will exist at some stage in the internal workings of the camera, even if it
does not emerge in that form. RGB consists of three parallel signals each having the same spectrum, and is used
where the highest accuracy is needed, often for production of still pictures. Examples of this are paint systems and
in computer aided design (CAD) displays. RGB is seldom used for real-time video recording.

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Figure 2.1: The major types of analog video. Red, green and blue signals emerge from the camera sensors,
needing full bandwidth. If a luminance signal is obtained by a weighted sum of R, G and B, it will need full
bandwidth, but the colour difference signals R–Y and B–Y need less bandwidth. Combining R–Y and B–Y into a
subcarrier modulation scheme allows colour transmission in the same bandwidth as monochrome.
Some compression can be obtained by using colour difference working. The human eye relies on brightness to
convey detail, and much less resolution is needed in the colour information. R,G and B are matrixed together to
form a luminance (and monochrome compatible) signal Y which has full bandwidth. The matrix also produces two
colour difference signals, R–Y and B–Y, but these do not need the same bandwidth as Y, one half or one quarter
will do depending on the application. Colour difference signals represent an early application of perceptive coding;
a saving in bandwidth is obtained by expressing the signals according to the way the eye operates.
Analog colour difference recorders such as Betacam and M II record these signals separately. The D-1 and D-5
formats record 525/60 or 625/50 colour difference signals digitally and Digital Betacam does so using compression.
In casual parlance, colour difference formats are often called component formats to distinguish them from
composite formats.
For colour television broadcast in a single channel, the PAL, SECAM and NTSC systems interleave into the
spectrum of a monochrome signal a subcarrier which carries two colour difference signals of restricted bandwidth.
As the bandwidth required for composite video is no greater than that of luminance, it can be regarded as a form of
compression performed in the analog domain. The artifacts which composite video introduces and the inflexibility in
editing resulting from the need to respect colour framing serve as a warning that compression is not without its
penalties. The subcarrier is intended to be invisible on the screen of a monochrome television set. A subcarrier-
based colour system is generally referred to as composite video, and the modulated subcarrier is called chroma.
It is not advantageous to compress composite video using modern transform-based coders as the transform
process cannot identify redundancy in a subcarrier. Composite video compression is restricted to differential coding
systems. Transform-based compression must use RGB or colour difference signals. As RGB requires excessive
bandwidth it makes no sense to use it with compression and so in practice only colour difference signals, which
have been bandwidth reduced by perceptive coding, are used in MPEG. Where signals to be compressed originate
in composite form, they must be decoded first. The decoding must be performed as accurately as possible, with
particular attention being given to the quality of the Y/C separation. The chroma in composite signals is deliberately
designed to invert from frame to frame in order to lessen its visibility. Unfortunately any residual chroma in
luminance will be interpreted by inter-field compression systems as temporal luminance changes which need to be
reproduced. This eats up data which should be used to render the picture. Residual chroma also results in high
horizontal and vertical spatial frequencies in each field which appear to be wanted detail to the compressor.
2.4 What is a digital signal?
One of the vital concepts to grasp is that digital audio and video are simply alternative means of carrying the same
information as their analog counterparts. An ideal digital system has the same characteristics as an ideal analog
system: both of them are totally transparent and reproduce the original applied waveform without error. Needless to
say, in the real world ideal conditions seldom prevail, so analog and digital equipment both fall short of the ideal.
Digital equipment simply falls short of the ideal to a smaller extent than does analog and at lower cost, or, if the

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designer chooses, can have the same performance as analog at much lower cost. Compression is one of the
techniques used to lower the cost, but it has the potential to lower the quality as well.
Any analog signal source can be characterized by a given useful bandwidth and signal-to-noise ratio. Video signals
have very wide bandwidth extending over several megaHertz but require only 50 dB or so SNR whereas audio
signals require only 20 kHz but need much better SNR.
Although there are a number of ways in which audio and video waveforms can be represented digitally, there is
one system, known as pulse code modulation (PCM) which is in virtually universal use. Figure 2.2 shows how PCM
works. Instead of being continuous, the time axis is represented in a discrete or stepwise manner. The waveform is
not carried by continuous representation, but by measurement at regular intervals. This process is called sampling
and the frequency with which samples are taken is called the sampling rate or sampling frequency Fs. The
sampling rate is generally fixed and is not necessarily a function of any frequency in the signal, although in
component video it will be line-locked for convenience. If every effort is made to rid the sampling clock of jitter, or
time instability, every sample will be made at an exactly even time step. Clearly if there are any subsequent
timebase errors, the instants at which samples arrive will be changed and the effect can be detected. If samples
arrive at some destination with an irregular timebase, the effect can be eliminated by storing the samples
temporarily in a memory and reading them out using a stable, locally generated clock. This process is called
timebase correction which all properly engineered digital systems employ. It should be stressed that sampling is an
analog process. Each sample still varies infinitely as the original waveform did.
Figure 2.2: In pulse code modulation (PCM) the analog waveform is measured periodically at the sampling rate.
The voltage (represented here by the height) of each sample is then described by a whole number. The whole
numbers are stored or transmitted rather than the waveform itself.
Figure 2.2 also shows that each sample is also discrete, or represented in a stepwise manner. The length of the
sample, which will be proportional to the voltage of the waveform, is represented by a whole number. This process
is known as quantizing and results in an approximation, but the size of the error can be controlled until it is
negligible. If, for example, we were to measure the height of humans to the nearest metre, virtually all adults would
register two metres high and obvious difficulties would result. These are generally overcome by measuring height
to the nearest centimetre. Clearly there is no advantage in going further and expressing our height in a whole
number of millimetres or even micrometres. An appropriate resolution can be found just as readily for audio or
video, and greater accuracy is not beneficial. The link between quality and sample resolution is explored later in
this chapter. The advantage of using whole numbers is that they are not prone to drift. If a whole number can be
carried from one place to another without numerical error, it has not changed at all. By describing waveforms
numerically, the original information has been expressed in a way which is better able to resist unwanted changes.
Essentially, digital systems carry the original waveform numerically. The number of the sample is an analog of time,
and the magnitude of the sample is an analog of the signal voltage. As both axes of the waveform are discrete, the
waveform can be accurately restored from numbers as if it were being drawn on graph paper. If we require greater
accuracy, we simply choose paper with smaller squares. Clearly more numbers are required and each one could
change over a larger range.
Discrete numbers are used to represent the value of samples so that they can readily be transmitted or processed
by binary logic. There are two ways in which binary signals can be used to carry sample data. When each digit of
the binary number is carried on a separate wire this is called parallel transmission. The state of the wires changes
at the sampling rate. This approach is used in the parallel video interfaces, as video needs a relatively short
wordlength; eight or ten bits. Using multiple wires is cumbersome where a long wordlength is in use, and a single
wire can be used where successive digits from each sample are sent serially. This is the definition of pulse code
modulation. Clearly the clock frequency must now be higher than the sampling rate.